Developing genome-wide SNPs and constructing an ultrahigh-density linkage map in oil palm

Multi-Omics Approaches in Oil Palm Research: A Comprehensive Review of Metabolomics, Proteomics, and Transcriptomics Based on Low-Temperature Stress

Oil palm (Elaeis guineensis Jacq.) is a typical tropical oil crop with a temperature of 26-28 °C, providing approximately 35% of the total world's vegetable oil. Growth and productivity are significantly affected by low-temperature stress, resulting in inhibited growth and substantial yield losses. To comprehend the intricate molecular mechanisms underlying the response and acclimation of oil palm under low-temperature stress, multi-omics approaches, including metabolomics, proteomics, and transcriptomics, have emerged as powerful tools. This comprehensive review aims to provide an in-depth analysis of recent advancements in multi-omics studies on oil palm under low-temperature stress, including the key findings from omics-based research, highlighting changes in metabolite profiles, protein expression, and gene transcription, as well as including the potential of integrating multi-omics data to reveal novel insights into the molecular networks and regulatory pathways involved in the response to low-temperature stress. This review also emphasizes the challenges and prospects of multi-omics approaches in oil palm research, providing a roadmap for future investigations. Overall, a better understanding of the molecular basis of the response of oil palm to low-temperature stress will facilitate the development of effective breeding and biotechnological strategies to improve the crop's resilience and productivity in changing climate scenarios.

Combination of GWAS and FST-based approaches identified loci associated with economic traits in sugarcane

Sugarcane is a globally important plant for both sugar and biofuel production. Although conventional breeding has played an important role in increasing the productivity of sugarcane, it takes a long time to achieve breeding goals such as high yield and resistant to diseases. Molecular breeding, including marker-assisted breeding and genomic selection, can accelerate genetic improvement by selecting elites at the seedling stage with DNA markers. However, only a few DNA markers associated with important traits were identified in sugarcane. The purpose of this study was to identify DNA markers associated with sugar content, stalk diameter, and sugarcane top borer resistance. The sugarcane samples with trait records were genotyped using the restriction site-associated DNA sequencing (RADseq) technology. Using F_ST analysis and genome-wide association study (GWAS), a total of 9, 23 and 9 DNA variants (single nucleotide polymorphisms (SNPs)/insertions and deletions (indels)) were associated with sugar content, stalk diameter, and sugarcane top borer resistance, respectively. The identified genetic variants were on different chromosomes, suggesting that these traits are complex and determined by multiple genetic factors. These DNA markers identified by both approaches have the potential to be used in selecting elite clones at the seeding stage in our sugarcane breeding program to accelerate genetic improvement. Certainly, it is essential to verify the reliability of the identified DNA markers associated with traits before they are used in molecular breeding in other populations.

Compatibility between snails and schistosomes: insights from new genetic resources, comparative genomics, and genetic mapping

The freshwater snail Biomphalaria glabrata is an important intermediate host of the parasite Schistosoma mansoni that causes human intestinal schistosomiasis. To better understand vector snail biology and help advance innovative snail control strategies, we have developed a new snail model consisting of two homozygous B. glabrata lines (iM line and iBS90) with sharply contrasting schistosome-resistance phenotypes. We produced and compared high-quality genome sequences for iM line and iBS90 which were assembled from 255 (N50 = 22.7 Mb) and 346 (N50 = 19.4 Mb) scaffolds, respectively. Using F2 offspring bred from the two lines and the newly generated iM line genome, we constructed 18 linkage groups (representing the 18 haploid chromosomes) covering 96% of the genome and identified three new QTLs (quantitative trait loci), two involved in snail resistance/susceptibility and one relating to body pigmentation. This study provides excellent genomic resources for unveiling complex vector snail biology, reveals genomic difference between resistant and susceptible lines, and offers novel insights into genetic mechanism of the compatibility between snail and schistosome.

Genome properties of key oil palm (Elaeis guineensis Jacq.) breeding populations

A good knowledge of the genome properties of the populations makes it possible to optimize breeding methods, in particular genomic selection (GS). In oil palm (Elaeis guineensis Jacq), the world's main source of vegetable oil, this would provide insight into the promising GS results obtained so far. The present study considered two complex breeding populations, Deli and La Mé, with 943 individuals and 7324 single-nucleotide polymorphisms (SNPs) from genotyping-by-sequencing. Linkage disequilibrium (LD), haplotype sharing, effective size (N_e), and fixation index (F_st) were investigated. A genetic linkage map spanning 1778.52 cM and with a recombination rate of 2.85 cM/Mbp was constructed. The LD at r²=0.3, considered the minimum to get reliable GS results, spanned over 1.05 cM/0.22 Mbp in Deli and 0.9 cM/0.21 Mbp in La Mé. The significant degree of differentiation existing between Deli and La Mé was confirmed by the high F_st value (0.53), the pattern of correlation of SNP heterozygosity and allele frequency among populations, and the decrease of persistence of LD and of haplotype sharing among populations with increasing SNP distance. However, the level of resemblance between the two populations over short genomic distances (correlation of r values between populations >0.6 for SNPs separated by <0.5 cM/1 kbp and percentage of common haplotypes >40% for haplotypes <3600 bp/0.20 cM) likely explains the superiority of GS models ignoring the parental origin of marker alleles over models taking this information into account. The two populations had low N_e (<5). Population-specific genetic maps and reference genomes are recommended for future studies.

Oil Palm Breeding in the Modern Era: Challenges and Opportunities

Oil palm, a cross-pollinated crop with long generation time, poses a lot of challenges in achieving sustainable oil palm with high yield and quality. The African oil palm (Elaeis guineensis Jacq.) is the most productive and versatile oil-yielding crop in the world, producing more than any other oil-yielding crop. Despite recent challenges, such as stress tolerance, superior oil quality, disease tolerance, and the need for new market niches, there is a growing need to explore and develop new varieties with high yield potential and the genetic diversity required to maintain oil palm yield stability. Breeding is an indispensable part of producing high-quality planting materials to increase oil palm yield. Biotechnological technologies have transformed conventional plant breeding approaches by introducing novel genotypes for breeding. Innovative pre-breeding and breeding approaches, such as identifying candidate genes in wild or land races using genomics tools, can pave the way for genetic improvement in oil palm. In this review, we highlighted the modern breeding tools, including genomics, marker-assisted breeding, genetic engineering, and genome editing techniques in oil palm crops, and we explored certain concerns connected to the techniques and their applications in practical breeding.

Predicting Heritability of Oil Palm Breeding Using Phenotypic Traits and Machine Learning

Oil palm is one of the main crops grown to help achieve sustainability in Malaysia. The selection of the best breeds will produce quality crops and increase crop yields. This study aimed to examine machine learning (ML) in oil palm breeding (OPB) using factors other than genetic data. A new conceptual framework to adopt the ML in OPB will be presented at the end of this paper. At first, data types, phenotype traits, current ML models, and evaluation technique will be identified through a literature survey. This study found that the phenotype and genotype data are widely used in oil palm breeding programs. The average bunch weight, bunch number, and fresh fruit bunch are the most important characteristics that can influence the genetic improvement of progenies. Although machine learning approaches have been applied to increase the productivity of the crop, most studies focus on molecular markers or genotypes for plant breeding, rather than on phenotype. Theoretically, the use of phenotypic data related to offspring should predict high breeding values by using ML. Therefore, a new ML conceptual framework to study the phenotype and progeny data of oil palm breeds will be discussed in relation to achieving the Sustainable Development Goals (SDGs).

Genomic Basis of Striking Fin Shapes and Colors in the Fighting Fish

Resolving the genomic basis underlying phenotypic variations is a question of great importance in evolutionary biology. However, understanding how genotypes determine the phenotypes is still challenging. Centuries of artificial selective breeding for beauty and aggression resulted in a plethora of colors, long-fin varieties, and hyper-aggressive behavior in the air-breathing Siamese fighting fish (Betta splendens), supplying an excellent system for studying the genomic basis of phenotypic variations. Combining whole-genome sequencing, quantitative trait loci mapping, genome-wide association studies, and genome editing, we investigated the genomic basis of huge morphological variation in fins and striking differences in coloration in the fighting fish. Results revealed that the double tail, elephant ear, albino, and fin spot mutants each were determined by single major-effect loci. The elephant ear phenotype was likely related to differential expression of a potassium ion channel gene, kcnh8. The albinotic phenotype was likely linked to a cis-regulatory element acting on the mitfa gene and the double-tail mutant was suggested to be caused by a deletion in a zic1/zic4 coenhancer. Our data highlight that major loci and cis-regulatory elements play important roles in bringing about phenotypic innovations and establish Bettas as new powerful model to study the genomic basis of evolved changes.

Molecular approaches for improving oil palm for oil

The oil palm, originating from Africa, is the most productive oil crop species. Palm oil is an important source of edible oil. Its current global plantation area is over 23 million ha. The theoretical oil yield potential of the oil palm is 18.2 tons/ha/year. However, current average oil yield is only 3.8 tons/ha/year. In the past 100 years, conventional breeding and improvement of field management played important roles in increasing oil yield. However, conventional breeding for trait improvement was limited by its very long (10-20 years) phenotypic selection cycle, although it improved oil yield by ~10-20% per generation. Molecular breeding using novel molecular technologies will accelerate genetic improvement and may reduce the need to deforest and to use arable land for expanding oil palm plantations, which in turn makes palm oil more sustainable. Here, we comprehensively synthesize information from relevant literature of the technologies, achievements, and challenges of molecular approaches, including tissue culture, haploid breeding, mutation breeding, marker-assisted selection (MAS), genomic selection (GS), and genome editing (GE). We propose the characteristics of ideal palms and suggest a road map to breed ideal palms for sustainable palm oil.

Reduced representation approach for identification of genome-wide SNPs and their annotation for economically important traits in Indian Tharparkar cattle

The present study was carried out in Tharparkar cattle for identification of genome-wide SNPs and microsatellites, and then annotate the identified high-quality SNPs to milk production, fertility, carcass, adaptability and immune response of economically important traits. A total of 146,011 SNPs were identified with respect to Bos taurus reference genome which are indicus specific, out of which 10,519 SNPs were found to be novel. Similarly, a total of 87,047 SNPs were identified with respect to Bos indicus reference genome. After final annotation of SNPs identified with respect to Bos indicus reference genome, 2871 SNPs were found to be associated in 383 candidate genes having to do with milk production, fertility, carcass, immune response and adaptability traits. Following that, 2571 microsatellites were identified. The information mined from the data might be of importance for the future breed improvement programs, conservation efforts and for enhancing the SNPs density of the existing bovine SNP chips.

Construction of a high density linkage map in Oil Palm using SPET markers

A high-density genetic linkage map from a controlled cross of two oil palm (Elaeis guineensis) genotypes was constructed based on Single Primer Enrichment Technology (SPET) markers. A 5K panel of hybridization probes were used for this purpose which was derived from previously developed SNP primers in oil palm. Initially, 13,384 SNPs were detected which were reduced to 13,073 SNPs after filtering for only bi-allelic SNP. Around 75% of the markers were found to be monomorphic in the progeny, reducing the markers left for linkage mapping to 3,501. Using Lep-MAP3 software, a linkage map was constructed which contained initially 2,388 markers and had a total length of 1,370 cM. In many cases several adjacent SNP were located on the same locus, due to missing recombination events between them, leading to a total of 1,054 loci on the 16 LG. Nevertheless, the marker density of 1.74 markers per cM (0.57 cM/marker) should allow the detection of QTLs in the future. This study shows that cost efficient SPET markers are suitable for linkage map construction in oil palm and probably, also in other species.

LD-annot: A Bioinformatics Tool to Automatically Provide Candidate SNPs With Annotations for Genetically Linked Genes

A multitude of model and non-model species studies have now taken full advantage of powerful high-throughput genotyping advances such as SNP arrays and genotyping-by-sequencing (GBS) technology to investigate the genetic basis of trait variation. However, due to incomplete genome coverage by these technologies, the identified SNPs are likely in linkage disequilibrium (LD) with the causal polymorphisms, rather than be causal themselves. In addition, researchers could benefit from annotations for the identified candidate SNPs and, simultaneously, for all neighboring genes in genetic linkage. In such case, LD extent estimation surrounding the candidate SNPs is required to determine the regions encompassing genes of interest. We describe here an automated pipeline, “LD-annot,” designed to delineate specific regions of interest for a given experiment and candidate polymorphisms on the basis of LD extent, and furthermore, provide annotations for all genes within such regions. LD-annot uses standard file formats, bioinformatics tools, and languages to provide identifiers, coordinates, and annotations for genes in genetic linkage with each candidate polymorphism. Although the focus lies upon SNP arrays and GBS data as they are being routinely deployed, this pipeline can be applied to a variety of datasets as long as genotypic data are available for a high number of polymorphisms and formatted into a vcf file. A checkpoint procedure in the pipeline allows to test several threshold values for linkage without having to rerun the entire pipeline, thus saving the user computational time and resources. We applied this new pipeline to four different sample sets: two breeding populations GBS datasets, one within-pedigree SNP set coming from whole genome sequencing (WGS), and a very large multi-varieties SNP dataset obtained from WGS, representing variable sample sizes, and numbers of polymorphisms. LD-annot performed within minutes, even when very high numbers of polymorphisms are investigated and thus will efficiently assist research efforts aimed at identifying biologically meaningful genetic polymorphisms underlying phenotypic variation. LD-annot tool is available under a GPL license from https://github.com/ArnaudDroitLab/LD-annot.

Dissecting Resistance to Phytophthora cinnamomi in Interspecific Hybrid Chestnut Crosses Using Sequence-Based Genotyping and QTL Mapping

The soilborne oomycete Phytophthora cinnamomi-which causes root rot, trunk cankers, and stem lesions on an estimated 5,000 plant species worldwide-is a lethal pathogen of American chestnut (Castanea dentata) as well as many other woody plant species. P. cinnamomi is particularly damaging to chestnut and chinquapin trees (Castanea spp.) in the southern portion of its native range in the United States due to relatively mild climatic conditions that are conductive to disease development. Introduction of resistant genotypes is the most practical solution for disease management in forests because treatment with fungicides and eradication of the pathogen are neither practical nor economically feasible in natural ecosystems. Using backcross families derived from crosses of American chestnuts with two resistant Chinese chestnut cultivars Mahogany and Nanking, we constructed linkage maps and identified quantitative trait loci (QTLs) for resistance to P. cinnamomi that had been introgressed from these Chinese chestnut cultivars. In total, 957 plants representing five cohorts of three hybrid crosses were genotyped by sequencing and phenotyped by standardized inoculation and visual examination over a 6-year period from 2011 to 2016. Eight parental linkage maps comprising 7,715 markers were constructed, and 17 QTLs were identified on four linkage groups (LGs): LG_A, LG_C, LG_E, and LG_K. The most consistent QTLs were detected on LG_E in seedlings from crosses with both 'Mahogany' and 'Nanking' and LG_K in seedlings from 'Mahogany' crosses. Two consistent large and medium effect QTLs located ∼10 cM apart were present in the middle and at the lower end of LG_E; other QTLs were considered to have small effects. These results imply that the genetic architecture of resistance to P. cinnamomi in Chinese chestnut × American chestnut hybrid progeny may resemble the P. sojae-soybean pathosystem, with a few dominant QTLs along with quantitatively inherited partial resistance conferred by multiple small-effect QTLs.

Linkage-based genome assembly improvement of oil palm (Elaeis guineensis)

Meiotic crossovers in outbred species, such as oil palm (Elaeis guineensis Jacq., 2n = 32) contribute to allelic re-assortment in the genome. Such genetic variation is usually exploited in breeding to combine positive alleles for trait superiority. A good quality reference genome is essential for identifying the genetic factors underlying traits of interest through linkage or association studies. At the moment, an AVROS pisifera genome is publicly available for oil palm. Distribution and frequency of crossovers throughout chromosomes in different origins of oil palm are still unclear. Hence, an ultrahigh-density genomic linkage map of a commercial Deli dura x AVROS pisifera family was constructed using the OP200K SNP array, to evaluate the genetic alignment with the genome assembly. A total of 27,890 linked SNP markers generated a total map length of 1,151.7 cM and an average mapping interval of 0.04 cM. Nineteen linkage groups represented 16 pseudo-chromosomes of oil palm, with 61.7% of the mapped SNPs present in the published genome. Meanwhile, the physical map was also successfully extended from 658 Mb to 969 Mb by assigning unplaced scaffolds to the pseudo-chromosomes. A genic linkage map with major representation of sugar and lipid biosynthesis pathways was subsequently built for future studies on oil related quantitative trait loci (QTL). This study improves the current physical genome of the commercial oil palm, and provides important insights into its recombination landscape, eventually unlocking the full potential genome sequence-enabled biology for oil palm.

Construction of a high-density linkage map and QTL mapping for important agronomic traits in Stylosanthes guianensis (Aubl.) Sw

Stylosanthes guianensis (Aubl.) Sw. is an economically important pasture and forage legume in tropical regions of the world. Genetic improvement of the crop can be enhanced through marker-assisted breeding. However, neither single nucleotide polymorphism (SNP) markers nor SNP-based genetic linkage map has been previously reported. In this study, a high-quality genetic linkage map of 2572 SNP markers for S. guianensis is generated using amplified-fragment single nucleotide polymorphism and methylation (AFSM) approach. The genetic map has 10 linkage groups (LGs), which spanned 2226.6 cM, with an average genetic distance of 0.87 cM between adjacent markers. Genetic mapping of quantitative trait loci (QTLs) for important agronomic traits such as yield-related and nutritional or quality-related traits was performed using F₂ progeny of a cross between a male-sterile female parent TPRC1979 and male parent TPRCR273 with contrasting phenotypes for morphological and physiological traits. A total of 30 QTLs for 8 yield-related traits and 18 QTLs for 4 nutritional or quality-related traits are mapped on the linkage map. Both the high-quality genetic linkage map and the QTL mapping for important agronomic traits described here will provide valuable genetic resources for marker-assisted selection for S. guianensis.

Experimental validation of in silico predicted RAD locus frequencies using genomic resources and short read data from a model marine mammal

BACKGROUND

Restriction site-associated DNA sequencing (RADseq) has revolutionized the study of wild organisms by allowing cost-effective genotyping of thousands of loci. However, for species lacking reference genomes, it can be challenging to select the restriction enzyme that offers the best balance between the number of obtained RAD loci and depth of coverage, which is crucial for a successful outcome. To address this issue, PredRAD was recently developed, which uses probabilistic models to predict restriction site frequencies from a transcriptome assembly or other sequence resource based on either GC content or mono-, di- or trinucleotide composition. This program generates predictions that are broadly consistent with estimates of the true number of restriction sites obtained through in silico digestion of available reference genome assemblies. However, in practice the actual number of loci obtained could potentially differ as incomplete enzymatic digestion or patchy sequence coverage across the genome might lead to some loci not being represented in a RAD dataset, while erroneous assembly could potentially inflate the number of loci. To investigate this, we used genome and transcriptome assemblies together with RADseq data from the Antarctic fur seal (Arctocephalus gazella) to compare PredRAD predictions with empirical estimates of the number of loci obtained via in silico digestion and from de novo assemblies.

RESULTS

PredRAD yielded consistently higher predicted numbers of restriction sites for the transcriptome assembly relative to the genome assembly. The trinucleotide and dinucleotide models also predicted higher frequencies than the mononucleotide or GC content models. Overall, the dinucleotide and trinucleotide models applied to the transcriptome and the genome assemblies respectively generated predictions that were closest to the number of restriction sites estimated by in silico digestion. Furthermore, the number of de novo assembled RAD loci mapping to restriction sites was similar to the expectation based on in silico digestion.

CONCLUSIONS

Our study reveals generally high concordance between PredRAD predictions and empirical estimates of the number of RAD loci. This further supports the utility of PredRAD, while also suggesting that it may be feasible to sequence and assemble the majority of RAD loci present in an organism's genome.

Genetic Mapping of the Incompatibility Locus in Olive and Development of a Linked Sequence-Tagged Site Marker

The genetic control of self-incompatibility (SI) has been recently disclosed in olive. Inter-varietal crossing confirmed the presence of only two incompatibility groups (G1 and G2), suggesting a simple Mendelian inheritance of the trait. A double digest restriction associated DNA (ddRAD) sequencing of a biparental population segregating for incompatibility groups has been performed and high-density linkage maps were constructed in order to map the SI locus and identify gene candidates and linked markers. The progeny consisted of a full-sib family of 229 individuals derived from the cross 'Leccino' (G1) × 'Dolce Agogia' (G2) varieties, segregating 1:1 (G1:G2), in accordance with a diallelic self-incompatibility (DSI) model. A total of 16,743 single nucleotide polymorphisms was identified, 7,006 in the female parent 'Leccino' and 9,737 in the male parent 'Dolce Agogia.' Each parental map consisted of 23 linkage groups and showed an unusual large size (5,680 cM in 'Leccino' and 3,538 cM in 'Dolce Agogia'). Recombination was decreased across all linkage groups in pollen mother cells of 'Dolce Agogia,' the parent with higher heterozygosity, compared to megaspore mother cells of 'Leccino,' in a context of a species that showed exceptionally high recombination rates. A subset of 109 adult plants was assigned to either incompatibility group by a stigma test and the diallelic self-incompatibility (DSI) locus was mapped to an interval of 5.4 cM on linkage group 18. This region spanned a size of approximately 300 Kb in the olive genome assembly. We developed a sequence-tagged site marker in the DSI locus and identified five haplotypes in 57 cultivars with known incompatibility group assignment. A combination of two single-nucleotide polymorphisms (SNPs) was sufficient to predict G1 or G2 phenotypes in olive cultivars, enabling early marker-assisted selection of compatible genotypes and allowing for a rapid screening of inter-compatibility among cultivars in order to guarantee effective fertilization and increase olive production. The construction of high-density linkage maps has led to the development of the first functional marker in olive and provided positional candidate genes in the SI locus.

Artificially designed hybrids facilitate efficient generation of high-resolution linkage maps

When sequencing eukaryotic genomes, linkage maps are indispensable for building scaffolds to assemble and/or to validate chromosomes. However, current approaches to constructing linkage maps are limited by marker density and cost-effectiveness, especially for wild organisms. We have now devised a new strategy based on artificially generated hybrid organisms to acquire ultrahigh-density genomic markers at reduced cost and build highly accurate linkage maps. We have also developed the novel analysis pipeline Scaffold Extender with Low Depth Linkage Analysis (SELDLA) for data processing to generate linkage maps and draft genomes. Using SELDLA, linkage maps and improved genomes for two species of pufferfish, Takifugu rubripes and Takifugu stictonotus, were obtained simultaneously. The strategy is applicable to a wide range of sexually reproducing organisms, and could, therefore, accelerate the whole genome analysis of various organisms including fish, mollusks, amphibians, insects, plants, and even mammals.